rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Uncertainty
    sub title: The Soul of Modeling, Probability & Statistics
  name:
    name part: Briggs, William.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2016
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIX, 258 p. 23 illus. online resource.
  abstract: This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance". The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, such as out-of-the-box regression, cannot help in discovering cause. This new way of looking at uncertainty ties together disparate fields — probability, physics, biology, the “soft” sciences, computer science — because each aims at discovering cause (of effects). It broadens the understanding beyond frequentist and Bayesian methods to propose a Third Way of modeling. Presents a complete argument showing why probability should be treated as a part of logic Broadens understanding beyond frequentist and Bayesian methods, proposing a Third Way of modeling Proposes that p-values should die, and along with them, hypothesis testing William M. Briggs, PhD, is Adjunct Professor of Statistics at Cornell University. Having earned both his PhD in Statistics and MSc in Atmospheric Physics from Cornell University, he served as the editor of the American Meteorological Society journal and has published over 60 papers. He studies the philosophy of science, the use and misuses of …
  table of contents: Truth, Argument, Realism -- Logic -- Induction and Intellection -- What Probability Is -- What Probability Is Not -- Chance and Randomness -- Causality -- Probability Models -- Statistical and Physical Models -- Modelling Goals, Strategies, and Mistakes.
  note: by William Briggs.
  subject:
    topic: Statistics
  subject:
    topic: Epistemology
  subject:
    topic: Logic
  subject:
    topic: Mathematics
    topic: Philosophy
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Philosophy of Mathematics
  subject:
    topic: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
  subject:
    topic: Epistemology
  subject:
    topic: Logic
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783319397566
  identifier: http://dx.doi.org/10.1007/978-3-319-39756-6
  record info:
    record creation date: 160630
    record change date: 20160630071359.0
    record identifier: 978-3-319-39756-6